By the same authors

Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner

Research output: Contribution to conferencePaper

Standard

Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner. / Sephton, Nicholas John; Cowling, Peter Ivan; Devlin, Sam; Hodge, Victoria Jane; Slaven, Nicholas H.

2016. Paper presented at IEEE Computational Intelligence and Games Conference (CIG 2016), Santorini, United Kingdom.

Research output: Contribution to conferencePaper

Harvard

Sephton, NJ, Cowling, PI, Devlin, S, Hodge, VJ & Slaven, NH 2016, 'Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner' Paper presented at IEEE Computational Intelligence and Games Conference (CIG 2016), Santorini, United Kingdom, 20/09/16 - 23/09/16, .

APA

Sephton, N. J., Cowling, P. I., Devlin, S., Hodge, V. J., & Slaven, N. H. (2016). Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner. Paper presented at IEEE Computational Intelligence and Games Conference (CIG 2016), Santorini, United Kingdom.

Vancouver

Sephton NJ, Cowling PI, Devlin S, Hodge VJ, Slaven NH. Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner. 2016. Paper presented at IEEE Computational Intelligence and Games Conference (CIG 2016), Santorini, United Kingdom.

Author

Sephton, Nicholas John ; Cowling, Peter Ivan ; Devlin, Sam ; Hodge, Victoria Jane ; Slaven, Nicholas H. / Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner. Paper presented at IEEE Computational Intelligence and Games Conference (CIG 2016), Santorini, United Kingdom.

Bibtex - Download

@conference{9fcc58d5418143f7a9bd10c67e61cdc5,
title = "Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner",
abstract = "As part of their design, card games often includeinformation that is hidden from opponents and represents astrategic advantage if discovered. A player that can discoverthis information will be able to alter their strategy based onthe nature of that information, and therefore become a morecompetent opponent. In this paper, we employ association rule-miningtechniques for predicting item multisets, and show themto be effective in predicting the content of Netrunner decks. Wethen apply different modifications based on heuristic knowledgeof the Netrunner game, and show the effectiveness of techniqueswhich consider this knowledge during rule generation andprediction.",
author = "Sephton, {Nicholas John} and Cowling, {Peter Ivan} and Sam Devlin and Hodge, {Victoria Jane} and Slaven, {Nicholas H}",
year = "2016",
month = "9",
day = "20",
language = "English",
note = "IEEE Computational Intelligence and Games Conference (CIG 2016) ; Conference date: 20-09-2016 Through 23-09-2016",

}

RIS (suitable for import to EndNote) - Download

TY - CONF

T1 - Using Association Rule Mining to Predict Opponent Deck Content in Android: Netrunner

AU - Sephton, Nicholas John

AU - Cowling, Peter Ivan

AU - Devlin, Sam

AU - Hodge, Victoria Jane

AU - Slaven, Nicholas H

PY - 2016/9/20

Y1 - 2016/9/20

N2 - As part of their design, card games often includeinformation that is hidden from opponents and represents astrategic advantage if discovered. A player that can discoverthis information will be able to alter their strategy based onthe nature of that information, and therefore become a morecompetent opponent. In this paper, we employ association rule-miningtechniques for predicting item multisets, and show themto be effective in predicting the content of Netrunner decks. Wethen apply different modifications based on heuristic knowledgeof the Netrunner game, and show the effectiveness of techniqueswhich consider this knowledge during rule generation andprediction.

AB - As part of their design, card games often includeinformation that is hidden from opponents and represents astrategic advantage if discovered. A player that can discoverthis information will be able to alter their strategy based onthe nature of that information, and therefore become a morecompetent opponent. In this paper, we employ association rule-miningtechniques for predicting item multisets, and show themto be effective in predicting the content of Netrunner decks. Wethen apply different modifications based on heuristic knowledgeof the Netrunner game, and show the effectiveness of techniqueswhich consider this knowledge during rule generation andprediction.

M3 - Paper

ER -